TFlearn is a modular and transparent deep learning library built on top of Tensorflow. It was designed to provide a higher-level API to TensorFlow in order to facilitate and speed-up experimentations, while remaining fully transparent and compatible with it.

Full transparency over Tensorflow. All functions are built over tensors and can be used independently of TFLearn.

Powerful helper functions to train any TensorFlow graph, with support of multiple inputs, outputs and optimizers.

Easy and beautiful graph visualization, with details about weights, gradients, activations and more...

Effortless device placement for using multiple CPU/GPU.

The high-level API currently supports most of recent deep learning models, such as Convolutions, LSTM, BiRNN, BatchNorm, PReLU, Residual networks, Generative networks... In the future, TFLearn is also intended to stay up-to-date with latest deep learning techniques.

Note: Latest TFLearn (v0.3) is only compatible with TensorFlow v1.0 and over.